This project is developing the first software to offer 3D visualization of health outcomes in a combined time and geography space, allowing the display of health data at multiple spatial and temporal scales within the same scene and thus taking full advantage of human visual perception that is fundamentally three dimensional. This visualization analytics environment will also provide an interface where the user can: 1) interact dynamically with the system (e.g. using data query, feature highlights, 3D scene rotation) and 2) contextualize the results, such as cancer burden, through the use of background maps that incorporate cues to the local context (e.g. orthophoto with names of major cities and highways to enhance the sense of place). This visualization module will be integrated into TerraSeer Space-Time Intelligence System" (STIS"), providing a comprehensive suite of tools for quantifying nested scales of spatial variation corresponding to individual ->neighborhood ->region, mapping disease incidence using both area-based and individual-level data, statistical analysis (e.g. cluster detection, regression) of health disparities, and detection of their changes in both space and time. A web- based mapping and data visualization system will also be developed to facilitate the use of this new technology by public health departments and increase the impact of the research. This project will accomplish four aims: 1. Conduct a requirements analysis to identify methods and functionality to incorporate into the software. 2. Explore the use of three-dimensional display and visual analytics for the representation and exploratory data analysis of health outcomes and their relationship to putative factors in both space and time. 3. Build and test a complete set of functionalities based on the research results, and incorporate them into Biomedware's space-time visualization and analysis technology (desktop and web-based applications) that will allow easy import and export of data layers with Google Earth Products. 4. Apply the software and methods to demonstrate the approach and its unique benefits for the investigation of geographic and temporal variations in cancer stage at diagnosis and survival data, and the exploration of relationships between health outcomes and potential factors, such as socio-economic conditions and proximity to screening facilities. These technologic, scientific and commercial innovations will revolutionize our ability to visualize and interpret variation in cancer incidence at multiple spatial scales and across time, which will help generating hypotheses for in depth individual studies of risk factors that are causal, or impact survival or morbidity, and establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. The creation of disease maps that accurately represent and contextualize the cancer burden will greatly facilitate their interpretation by local communities and engage their participation in addressing health disparities. PUBLIC HEALTH RELEVANCE: The substantial benefit of this research is its utility in accessing and linking diverse individual-level and population-based data, followed by the three-dimensional visualization, interactive analysis and contextual mapping of variation in cancer incidence and mortality at multiple spatial scales and across time. The methods developed in this project will help generating hypotheses for in depth individual studies of risk factors that are causal, or impact survival or morbidity, and establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. The incorporation of these innovative visualization and mapping tools into TerraSeer Space-Time Intelligence System" (STIS"), along with the development of a Web-based application, will help public health departments communicate more effectively the results of their analysis to local communities and develop participatory strategies to facilitate the translation of research results into interventions to alleviate the problems identified.